Asish Biswas · Munich, Germany
From raw data to boardroom-ready decisions.
I lead analytics platforms and BI delivery end-to-end — architecture to adoption. 14+ years in insurance and automotive, now seeking a Solution Architect / Product Owner / Sr. Data Engineer role in DACH.
14+
years in data & analytics
3
industries: insurance, automotive, aviation
4
credentials: EMBA, MSc, AWS SA, SAFe PO
5
platforms: Databricks, Azure, AWS, Palantir, Snowflake
14 years, one throughline: owning data end to end
From C++ middleware at Amadeus, through cloud-migrated ML pipelines at BMW, to leading the enterprise Data Asset platform at Allianz Commercial — I've consistently taken data projects from architecture through delivery to adoption.
See the full profileOpen to roles like...
- Product Owner — Data & Analytics
- Sr. Data Engineer
- Analytics / BI Lead
- Solution Architect — Data Platforms
Also available for analytics consulting
For teams that need a data platform, BI dashboards, or customer analytics built or fixed.
Analytics Platform Build & Modernization
Bring your data together. Build a foundation your business can trust.
Insurance Analytics
Connected insights across distribution, underwriting, and claims.
Customer Analytics
Understand your customers. Focus on the relationships that drive value.
Dashboards & Business Steering BI
See what matters. Understand what changed. Know where to act.
A sample of the dashboards I build
Synthetic data, same approach: KPIs tied to a decision, not just displayed. This is illustrative only — no client data.
Example: quarterly sales steering trend (synthetic data)
Insights
Read more →Why Most BI Dashboards Fail Before They're Even Built
The usual failure mode isn't bad visualization — it's starting with the data instead of the decision. A look at how to define the KPI and the owning decision first, then build the dashboard around that.
Medallion Architecture, Explained for the Business Side
Bronze, silver, gold: what a medallion data architecture actually buys a non-technical stakeholder in terms of trust, speed, and governance — without the engineering jargon.
What GDPR-Compliant Data Governance Actually Looks Like in Practice
ABAC, PII masking, and data contracts are easy to name and hard to implement well. Notes from building a governance framework inside a regulated data lake.